To improve satellite acquisition and tracking performance, it is a main trend that most of the modernized GNSS will utilize a pilot signal as an aid. That is, in addition to a data signal carrying navigation messages, each satellite in the GNSS further transmits a pilot signal to enhance weak signal tracking. Such modernized GNSS include new generation GPS (Global Positioning System) (e.g. L1C, L2C, L5 bands), Galileo (e.g. E5ab, E6C bands, and L1F, also referred to as E1), and Compass Satellite System.
As mentioned, the data signal carries the navigation messages of a form of unknown data. The pilot signal is “dataless”. That is, the content of the pilot signal is known and deterministic. The data signal and pilot signal are respectively modulated with different ranging codes. Moreover, the data signal is modulated with a stream of navigation data frames. The pilot signal is modulated by a periodic secondary code sequence. On the other hand, the pilot signal of some GNSS systems is not modulated by the secondary code sequence. Although the formats of the data and pilot signals are different from each other, timing relationship between the data and pilot signals is in-phase. To demodulate the data carried in the data signal, it is necessary to determine the phase of the leading edge of each frame, that is, to determine the boundary of the frame. Determination of the frame boundary (i.e. the leading edge) is referred to as “frame sync”. In addition, it is also necessary to carry out “pilot sync”, which means to find the phase of the secondary code modulating the pilot signal, that is, to determine the leading edge of the secondary code sequence.
In general, each frame of the data signal has a sync word or the like. Once the position of the sync word is determined, the frame boundary is found. However, the data carried by the data signal is random. It is possible that the pattern of the sync word also appears in the random data, and thereby resulting in false alarm for the frame sync. Another cause which may result in false alarm of frame sync is noise.
Conventionally, the received data symbols are correlated with possible hypotheses to determine the frame boundary. Therefore, correlation computation load is quite heavy. In addition, a requirement for relevant hardware such as correlators, buffers, processors and so on consumes high costs. For Galileo E1, there are 250 frame sync hypotheses for the data signal E1B since each frame of the E1B consists of 250 symbols. There are 25 pilot sync hypotheses for the pilot signal E1C since each secondary code sequence has 25 symbols. The most possible hypotheses are sieved from correlation results, and the sieved hypotheses are verified by further signal processing such as Viterbi decoding, CRC and so on. As known, those signal processing schemes are very complex and take a long period of time to process.
It is desirable to reduce the computation complexity and to reduce false alarm probability when carrying out the frame sync/pilot sync. The present invention provides an effective solution to satisfy such requirements.